Patient Characteristics Associated With Using Transcatheter Left Atrial Appendage Occlusion Versus Oral Anticoagulants for Atrial Fibrillation.

BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to oral anticoagulants (OACs) for stroke prevention in patients with atrial fibrillation, but the predictors of LAAO use in routine care are unclear. We aimed to assess the utilization trends of LAAO and compare the change in characteristics of LAAO users versus OACs since its marketing. METHODS: Using the US Medicare claims database (March 15, 2015, to December 31, 2020), we identified patients with atrial fibrillation, ≥65 years, and CHA2DS2-VASc score ≥2 (men) or ≥3 (women), with either first implantation of an LAAO device or initiation of OACs, including apixaban, dabigatran, rivaroxaban, edoxaban, or warfarin. Patient characteristics, measured 365 days before the first LAAO or OAC use date, were compared using logistic regression. RESULTS: There were 30 058 LAAO recipients (mean age, 77.74 years; female, 42.1%) and 792 600 OAC initiators (mean age, 78.48; female, 53.3%). In 2020, patients had higher odds of initiating LAAO use than in 2015 (0.52 versus 9.32%; adjusted odds ratio [aOR], 13.64 [95% CI, 12.56-14.81]). Old age (ie, >85 versus 65-75 years; aOR, 0.84 [95% CI, 0.80-0.88]), female sex (aOR, 0.74 [95% CI, 0.71-0.76]), Black race (aOR, 0.63 [95% CI, 0.58-0.68]) versus White race, and Medicaid eligibility (aOR, 0.61 [95% CI, 0.58-0.64]) were associated with lower odds of receiving LAAO. Among clinical characteristics, frailty, cancer, fractures, and venous thromboembolism were associated with lower odds of LAAO use, while history of intracranial and extracranial bleeding, coagulopathy, and falls were associated with higher odds of receiving LAAO. CONCLUSIONS: Among patients with atrial fibrillation receiving stroke-preventive therapy, LAAO use increased rapidly from 2015 to 2020 and was positively associated with the risk factors for OAC complications but negatively associated with old age, advanced frailty, and cancer. Black race and female sex were associated with a lower likelihood of receiving LAAO.

Development and Validation of a Claims-Based Model to Predict Categories of Obesity.

We developed and validated a claims-based algorithm that classifies patients into obesity categories. Using Medicare (2007-2017) and Medicaid (2000-2014) claims data linked to 2 electronic health record (EHR) systems in Boston, Massachusetts, we identified a cohort of patients with an EHR-based body mass index (BMI) measurement (calculated as weight (kg)/height (m)2). We used regularized regression to select from 137 variables and built generalized linear models to classify patients with BMIs of ≥25, ≥30, and ≥40. We developed the prediction model using EHR system 1 (training set) and validated it in EHR system 2 (validation set). The cohort contained 123,432 patients in the Medicare population and 40,736 patients in the Medicaid population. The model comprised 97 variables in the Medicare set and 95 in the Medicaid set, including BMI-related diagnosis codes, cardiovascular and antidiabetic drugs, and obesity-related comorbidities. The areas under the receiver-operating-characteristic curve in the validation set were 0.72, 0.75, and 0.83 (Medicare) and 0.66, 0.66, and 0.70 (Medicaid) for BMIs of ≥25, ≥30, and ≥40, respectively. The positive predictive values were 81.5%, 80.6%, and 64.7% (Medicare) and 81.6%, 77.5%, and 62.5% (Medicaid), for BMIs of ≥25, ≥30, and ≥40, respectively. The proposed model can identify obesity categories in claims databases when BMI measurements are missing and can be used for confounding adjustment, defining subgroups, or probabilistic bias analysis.

Rates and costs of drug testing practices for private payors in the outpatient setting in the United States, 2015-2019.

INTRODUCTION: Clinical practice guidelines recommend drug testing patients who are receiving opioids chronically for pain or medication for a substance use disorder (SUD)-particularly opioid use disorder (OUD)-but practices vary due to a lack of consensus on testing frequency during follow-up. This study aimed to evaluate rates and costs of outpatient drug testing practices for patients receiving opioids for chronic pain or medication for an SUD. METHODS: Using claims data from a large de-identified claims data warehouse, we conducted a retrospective cohort study of chronic opioid, buprenorphine, and naltrexone users between January 2015 and December 2019. We identified two cohorts-chronic opioid medication cohort (CO) and SUD-indicated medication cohort (SUD). We assessed drug testing rates during follow-up using procedure codes and costs using copayment, deductible, co-insurance, and out-of-pocket data. RESULTS: Among 6,657,515 eligible claimants, 367,118 (5.5 %) received opioids chronically and 73,303 (1.1 %) received an SUD-indicated medication. The cumulative proportion of drug testing during follow-up was similar between cohorts (CO: 36 %; SUD: 35 %), but rate of testing was consistently twice as frequent for the SUD cohort. All cost variables for the first drug test were higher on average in the SUD cohort than the CO cohort except copay: deductible (SUD: $18.54; CO: $7.33); co-insurance (SUD: $10.36; CO: $2.53); out-of-pocket (SUD: $29.39; CO: $10.57); copay (CO: $0.71; SUD: $0.49) (all p < 0.001). CONCLUSIONS: Overall proportion of drug testing was similar between cohorts, but testing frequency was at least double during follow-up in the SUD cohort. Most cost variables were higher in the SUD cohort. Whether the high cost of drug testing is a barrier to medication use or is associated with treatment discontinuation should be evaluated.

Frailty and uptake of angiotensin receptor neprilysin inhibitor for heart failure with reduced ejection fraction.

BACKGROUND: Frail older adults may be less likely to receive guideline-directed medical therapy (GDMT)-renin-angiotensin blockers, beta-blockers, and mineralocorticoid receptor antagonists-for heart failure with reduced ejection fraction (HFrEF). We aimed to examine the uptake of angiotensin receptor neprilysin inhibitor (ARNI) and GDMT in frail older adults with HFrEF. METHODS: Using 2015-2019 Medicare data, we estimated the proportion of beneficiaries with HFrEF receiving ARNI and GDMT each year by frailty status, defined by a claims-based frailty index. Logistic regression was used to identify clinical characteristics associated with ARNI initiation. Cox proportional hazards regression was used to examine the association of GDMT use in 2015 and death or heart failure hospitalization in 2016-2019. RESULTS: Among 147,506-180,386 beneficiaries with HFrEF (mean age: 77 years; 27% women; 42.6-49.1% frail) in 2015-2019, the proportion of patients receiving ARNI increased in both non-frail (0.4%-16.4%) and frail (0.3%-13.7%) patients (p for yearly-trend-by-frailty = 0.970). Among those not receiving a renin-angiotensin system blocker, patients with age ≥ 85 years (odds ratio [95% CI], 0.89 [0.80-0.99]), dementia (0.88 [0.81-0.96]), and frailty (0.87 [0.81-0.94]) were less likely to initiate ARNI. The proportion of patients receiving all 3 GDMT classes increased in non-frail patients (22.0%-27.0%) but changed minimally in frail patients (19.6%-21.8%). Regardless of frailty status, treatment with at least 1 class of GDMT was associated with lower death or heart failure hospitalization than no GDMT medications (hazard ratio [95% CI], 0.94 [0.91-0.97], 0.92 [0.89-0.94], 0.94 [0.91-0.97] for 1, 2, and 3 classes, respectively). CONCLUSIONS: Our results suggest an evidence-practice gap in the use of ARNI and GDMT in Medicare beneficiaries with HFrEF, particularly those with frailty. Efforts to narrow this gap are needed to reduce the burden of HFrEF in older adults.

A Novel Chronic Kidney Disease Phenotyping Algorithm Using Combined Electronic Health Record and Claims Data.

Purpose: Because chronic kidney disease (CKD) is often under-coded as a diagnosis in claims data, we aimed to develop claims-based prediction models for CKD phenotypes determined by laboratory results in electronic health records (EHRs). Patients and Methods: We linked EHR from two networks (used as training and validation cohorts, respectively) with Medicare claims data. The study cohort included individuals ≥65 years with a valid serum creatinine result in the EHR from 2007 to 2017, excluding those with end-stage kidney disease or on dialysis. We used LASSO regression to select among 134 predictors for predicting continuous estimated glomerular filtration rate (eGFR). We assessed the model performance when predicting eGFR categories of <60, <45, <30 mL/min/1.73m2 in terms of area under the receiver operating curves (AUC). Results: The model training cohort included 117,476 patients (mean age 74.8 years, female 58.2%) and the validation cohort included 56,744 patients (mean age 73.8 years, female 59.6%). In the validation cohort, the AUC of the primary model (with 113 predictors and an adjusted R2 of 0.35) for predicting eGFR <60, eGFR<45, and eGFR <30 mL/min/1.73m2 categories was 0.81, 0.88, and 0.92, respectively, and the corresponding positive predictive values for these 3 phenotypes were 0.80 (95% confidence interval: 0.79, 0.81), 0.79 (0.75, 0.84), and 0.38 (0.30, 0.45), respectively. Conclusion: We developed a claims-based model to determine clinical phenotypes of CKD stages defined by eGFR values. Researchers without access to laboratory results can use the model-predicted phenotypes as a proxy clinical endpoint or confounder and to enhance subgroup effect assessment.

Scalable Feature Engineering from Electronic Free Text Notes to Supplement Confounding Adjustment of Claims-Based Pharmacoepidemiologic Studies.

Natural language processing (NLP) tools turn free-text notes (FTNs) from electronic health records (EHRs) into data features that can supplement confounding adjustment in pharmacoepidemiologic studies. However, current applications are difficult to scale. We used unsupervised NLP to generate high-dimensional feature spaces from FTNs to improve prediction of drug exposure and outcomes compared with claims-based analyses. We linked Medicare claims with EHR data to generate three cohort studies comparing different classes of medications on the risk of various clinical outcomes. We used "bag-of-words" to generate features for the top 20,000 most prevalent terms from FTNs. We compared machine learning (ML) prediction algorithms using different sets of candidate predictors: Set1 (39 researcher-specified variables), Set2 (Set1 + ML-selected claims codes), and Set3 (Set1 + ML-selected NLP-generated features), vs. Set4 (Set1 + 2 + 3). When modeling treatment choice, we observed a consistent pattern across the examples: ML models utilizing Set4 performed best followed by Set2, Set3, then Set1. When modeling the outcome risk, there was little to no improvement beyond models based on Set1. Supplementing claims data with NLP-generated features from free text notes improved prediction of prescribing choices but had little or no improvement on clinical risk prediction. These findings have implications for strategies to improve confounding using EHR data in pharmacoepidemiologic studies.

Medication Burden and Prescribing Patterns in Patients on Hemodialysis in the USA, 2013-2017.

INTRODUCTION: The medication burden of patients with end-stage renal disease (ESRD) on hemodialysis, a patient population with a high comorbidity burden and complex care requirements, is among the highest of any of the chronic diseases. The goal of this study was to describe the medication burden and prescribing patterns in a contemporary cohort of patients with ESRD on hemodialysis in the USA. METHODS: We used the United States Renal Data System database from January 1, 2013, and December 31, 2017, to quantify the medication burden of patients with ESRD on hemodialysis aged ≥18 years. We calculated the average number of prescription medications per patient during each respective year (January-December), number of medications within classes, including potentially harmful medications, and trends in the number of medications and classes over the 5-year study period. RESULTS: We included a total of 163,228 to 176,133 patients from 2013 to 2017. The overall medication burden decreased slightly, from a mean of 7.4 (SD 3.8) medications in 2013 to 6.8 (SD 3.6) medications in 2017. Prescribing of potentially harmful medications decreased over time (74.0% with at least one harmful medication class in 2013-68.5% in 2017). In particular, the prescribing of non-benzodiazepine hypnotics, benzodiazepines, and opioids decreased from 2013 to 2017 (12.2%-6.3%, 23.4%-19.3%, and 60.0%-53.4%, respectively). This trend was consistent across subgroups of age, sex, race, and low-income subsidy status. CONCLUSIONS: Patients with ESRD on hemodialysis continued to have a high overall medication burden, with a slight reduction over time accompanied by a decrease in prescribing of several classes of harmful medications. Continued emphasis on assessment of appropriateness of high medication burden in patients with ESRD is needed to avoid exposure to potentially harmful or futile medications in this patient population.

Associations Between Copays, Coverage Limits for Opioid Use Disorder Medications, and Prescribing in Medicaid, 2018.

BACKGROUND: Opioid use disorder (OUD) affects millions of Americans, but only a fraction receive treatment. Many patients with OUD are enrolled in Medicaid, but elements of different state Medicaid programs' drug benefit designs may impact patients' access to life-saving care. OBJECTIVE: To describe medication for OUD (mOUD) use in Medicaid and examine the relationship between mOUD use and state drug benefit design plans. DESIGN/SUBJECTS: Cross-sectional study using Medicaid State Drug Utilization Data from 2018 to quantify office-based mOUD and the Medicaid Behavioral Health Services Database to extract copay amounts and coverage limits for mOUD. We excluded states with <5% coverage and assessed for associations between copays or coverage limits and mOUD dispensing using simple linear regression. MEASURES: Proportion of mOUD prescriptions relative to all prescriptions, opioid prescriptions, and the state-level prevalence of pain reliever use disorder and association between copays, coverage limits and these proportions. RESULTS: There was substantial variability in mOUD use. Although state Medicaid drug benefit designs also varied, we found no significant relationship between copay requirements (yes/no), coverage limits (yes/no), copay amount ($0-$0.99 vs. $1 or more), and mOUD utilization measures. CONCLUSIONS: Substantial state-level variation exists in mOUD use, but we did not find a significant association between copays or coverage limits and use in Medicaid. Further research is needed to assess other potential impacts of mOUD drug benefit design elements in Medicaid.

Risk of Cataract Surgery and Age-Related Macular Degeneration After Initiation of Denosumab vs Zoledronic Acid for Osteoporosis: A Multi-Database Cohort Study.

BACKGROUND AND OBJECTIVE: There is a relative lack of head-to-head comparisons of denosumab against other osteoporosis drugs on safety. We aimed to explore ocular outcomes in patients with osteoporosis initiating denosumab vs zoledronic acid. METHODS: We conducted a cohort study using claims data (2010-15) from two large US commercial insurance databases including patients with osteoporosis who were aged 50 years or older and initiators of denosumab or zoledronic acid. The primary outcomes were (1) receipt of cataract surgery and development of (2) wet age-related macular degeneration and (3) dry age-related macular degeneration within 365 days after initiation of denosumab vs zoledronic acid. Propensity score fine stratification and weighting were used to control for potential confounding, and we calculated the incidence rate and hazard ratio for each outcome in the cohorts. The estimates from the two databases were combined with a fixed-effects model meta-analysis. RESULTS: The study cohort included 50,821 denosumab and 67,471 zoledronic acid initiators. In the propensity score-weighted analysis, compared to zoledronic acid use, denosumab was associated with a modestly decreased risk of undergoing cataract surgery (hazard ratio 0.91; 95% confidence interval 0.85-0.98) but not with the risk of wet age-related macular degeneration (hazard ratio 1.29; 95% confidence interval 0.99-1.70) or dry age-related macular degeneration (hazard ratio 1.03; 95% confidence interval 0.98-1.09). CONCLUSIONS: In this large population-based cohort study of 118,292 patients with osteoporosis, initiation of denosumab was associated with a modestly decreased risk of cataract surgery vs zoledronic acid. The risk of age-related macular degeneration was similar between the two drugs.

Characteristics of early sacubitril/valsartan patients and considerations for studies in electronic health record data.

AIM: We examined characteristics of early sacubitril/valsartan users in a large US electronic health records database. PATIENTS & METHODS: We identified three cohorts of patients with heart failure (HF): sacubitril/valsartan patients with a prior HF diagnosis; patients with HF with reduced ejection fraction; and patients with HF treated with an angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker and a ß-blocker. RESULTS: Sacubitril/valsartan patients were younger than patients in the other cohorts; the mean age of sacubitril/valsartan patients increased by 2 years in the first 15 months of marketing. Most sacubitril/valsartan patients had prior use of HF treatment. CONCLUSION: Overall, sacubitril/valsartan patients resembled those in the HF with reduced ejection fraction cohort, and commonly used other drugs for HF.

Association of Medicare's Bundled Payment Reform With Changes in Use of Vitamin D Among Patients Receiving Maintenance Hemodialysis: An Interrupted Time-Series Analysis.

BACKGROUND & RATIONALE: Medicare's 2011 prospective payment system (PPS) was introduced to curb overuse of separately billable injectable drugs. After epoietin, intravenous (IV) vitamin D analogues are the biggest drug cost drivers in hemodialysis (HD) patients, but the association between PPS introduction and vitamin D therapy has been scarcely investigated. STUDY DESIGN: Interrupted time-series analyses. SETTING & PARTICIPANTS: Adult US HD patients represented in the US Renal Data System between 2008 and 2013. EXPOSURES: PPS implementation. OUTCOMES: The cumulative dose of IV vitamin D analogues (paricalcitol equivalents) per patient per calendar quarter in prevalent HD patients. The average starting dose of IV vitamin D analogues and quarterly rates of new vitamin D use (initiations/100 person-months) in incident HD patients within 90 days of beginning HD therapy. ANALYTICAL APPROACH: Segmented linear regression models of the immediate change and slope change over time of vitamin D use after PPS implementation. RESULTS: Among 359,600 prevalent HD patients, IV vitamin D analogues accounted for 99% of the total use, and this trend was unchanged over time. PPS resulted in an immediate 7% decline in the average dose of IV vitamin D analogues (average baseline dose = 186.5 µg per quarter; immediate change = -13.5 µg [P < 0.001]; slope change = 0.43 per quarter [P = 0.3]) and in the starting dose of IV vitamin D analogues in incident HD patients (average baseline starting dose = 5.22 µg; immediate change = -0.40 µg [P < 0.001]; slope change = -0.03 per quarter [P = 0.03]). The baseline rate of vitamin D therapy initiation among 99,970 incident HD patients was 44.9/100 person-months and decreased over time, even before PPS implementation (pre-PPS ß = -0.46/100 person-months [P < 0.001]; slope change = -0.19/100 person-months [P = 0.2]). PPS implementation was associated with an immediate change in initiation levels (by -4.5/100 person-months; P < 0.001). LIMITATIONS: Incident HD patients were restricted to those 65 years or older. CONCLUSION: PPS implementation was associated with a 7% reduction in the average dose and starting dose of IV vitamin D analogues and a 10% reduction in the rate of vitamin D therapy initiation.

Comparative Safety and Effectiveness of Denosumab Versus Zoledronic Acid in Patients With Osteoporosis: A Cohort Study.

Limited head-to-head comparative safety and effectiveness data exist between denosumab and zoledronic acid in real-world healthcare. We aimed to examine the safety and effectiveness of denosumab compared to zoledronic acid with regard to risk of serious infection and cardiovascular disease (CVD) and osteoporotic fracture. We conducted a cohort study using claims data (2009-2013) from a US commercial insurance plan database. We included patients aged ≥50 years who were newly initiated on denosumab or zoledronic acid. The primary outcomes were (1) hospitalization for serious infection; (2) composite CVD endpoint including myocardial infarction, stroke, coronary revascularization, and heart failure; and (3) nonvertebral osteoporotic fracture including hip, wrist, forearm, and pelvic fracture. To control for potential confounders, we used 1:1 propensity score (PS) matching. Cox proportional hazards models compared the risk of serious infection, CVD, and osteoporotic fracture within 365 days after initiation of denosumab versus zoledronic acid. After PS matching, a total of 2467 pairs of denosumab and zoledronic acid initiators were selected with a mean age of 63 years and 96% were female. When compared with zoledronic acid, denosumab was not associated with an increased risk of serious infection (HR 0.81; 95% confidence interval [CI], 0.55 to 1.21) or CVD (HR 1.11; 95% CI, 0.60 to 2.03). Similar results were obtained for each component of CVD. The risk of osteoporotic fracture was also similar between groups (HR 1.21; 95% CI, 0.84 to 1.73). This large population-based cohort study shows that denosumab and zoledronic acid have comparable clinical safety and effectiveness with regard to the risk of serious infection, CVD, and osteoporosis fracture within 365 days after initiation of medications. © 2016 American Society for Bone and Mineral Research.